Artificial Intelligence Engineer

AI Engineer (Agentic Systems Focus)

A highly technical role within a large, data-driven organization seeking an engineer to design and scale agentic AI systems and intelligent applications. This position focuses on building production-grade AI systems that enable autonomous decision-making, multi-step reasoning, and workflow automation across enterprise environments.

Core Responsibilities

Agentic AI & LLM Systems

• Design and deploy agent-based systems capable of multi-step reasoning, tool usage, and autonomous execution
• Build workflows using LangChain, LangGraph, LlamaIndex, or similar frameworks
• Implement tool-calling architectures integrating APIs, databases, and enterprise systems
• Develop multi-agent workflows, prompt strategies, and evaluation frameworks

RAG & Knowledge Systems

• Build RAG pipelines using enterprise data (structured and unstructured)
• Design embedding strategies, retrieval pipelines, and context optimization
• Manage vector databases (Pinecone, Weaviate, pgvector, etc.)
• Enable semantic search and enterprise AI copilots

AI Systems & Infrastructure

• Architect systems supporting stateful agents, memory, and real-time decisioning
• Integrate AI into business workflows and enterprise systems
• Establish guardrails, observability, and reliability standards

LLMOps & Production

• Deploy AI systems in cloud environments (AWS, Azure, GCP)
• Build CI/CD pipelines for LLMs, agents, and data workflows
• Implement monitoring, evaluation, and feedback loops

Applications & Interfaces

• Build AI-powered tools, copilots, and assistant interfaces
• Integrate backend AI systems into scalable user-facing applications

Required Experience

• 8+ years in software, data, or ML engineering
• Strong Python experience (production-level)
• Hands-on experience with LLMs, RAG systems, and agentic workflows
• Experience with LangChain, LangGraph, LlamaIndex, or similar tools
• Familiarity with vector databases and embedding pipelines
• Experience with cloud platforms (AWS, Azure, or GCP)
• Strong background in API development and scalable systems
• Experience with LLMOps / MLOps practices

What This Role Owns

Build and scale agent-driven AI systems that move beyond static models — enabling systems that can reason, act, and continuously improve across the enterprise.